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  • SB Königs Wusterhausen  (2)
  • Hertie School  (2)
  • Wissenschaftspark Albert Einstein  (1)
  • SB Schlieben
  • 2020-2024  (5)
Type of Medium
Language
Region
Library
Year
Subjects(RVK)
Keywords
  • 1
    Book
    Book
    Berlin : Suhrkamp
    UID:
    kobvindex_ZLB34836785
    Format: 367 Seiten , 18.8 cm x 11.8 cm, 256 g
    Edition: Erste Auflage
    ISBN: 9783518471906 , 3518471902
    Series Statement: suhrkamp taschenbuch 5190
    Note: In Beziehung stehende Ressource: 9783518428559 (ISBN) , In Beziehung stehende Ressource: 9783518469750 (ISBN) , In Beziehung stehende Ressource: 9783518470572 (ISBN) , Erscheint auch als Online-Ausgabe 9783518428900 (ISBN) , Erscheint auch als Online-Ausgabe 9783518756683 (ISBN)
    Language: German
    Author information: Enzensberger, Hans Magnus
    Author information: Bexte, Bernd
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    gbv_1765639069
    Note: Master Thesis Hertie School, Berlin 2021
    Language: English
    Keywords: Hochschulschrift
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    UID:
    gbv_1802250174
    Format: XI, 226 Seiten , Diagramme, Grafiken
    ISBN: 9789004519367
    Series Statement: China studies volume 48
    Content: "Why has China's authoritarian government under Xi Jinping retained popular support without political reforms? Drawing on Chinese social media data, in this book Titus C. Chen argues that China's digital propaganda and information control techniques--the monopolistic exercise of market authoritarianism--have empowered the Xi administration to manipulate public discourse and shape public opinion via social media. Chen argues that these techniques forge a sense of community and unite the general public under the Chinese government, thereby legitimating autocratic rule. By enhancing our understanding of China's digital ideological statecraft, the book makes a major contribution to the fields of China Studies and Political Communication."--
    Note: Literaturverzeichnis Seite 187-221 , Register Seite 222-226
    Additional Edition: ISBN 9789004519374
    Additional Edition: Erscheint auch als Online-Ausgabe Chen, Titus C. The making of a neo-propaganda state Leiden : Brill, 2022 ISBN 9789004519374
    Language: English
    Subjects: Political Science
    RVK:
    RVK:
    Library Location Call Number Volume/Issue/Year Availability
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  • 4
    UID:
    kobvindex_VBRD-i97835934502610534
    Format: 534 S.
    ISBN: 9783593450261
    Content: Eine Chinesin, die es wagt, ihren brasilianischen Freund nicht mehr länger nur in einer virussicheren, virtuellen Realität zu treffen. Ein junger Mann in Sri Lanka, der mittels autonomer Fahrzeuge Leben rettet. Ein Münchner Quantencomputerprofi, der die Welt mit KI-gesteuerten Waffen ins Chaos stürzen will ... In KI 2041 haben sich der international bekannteste KI-Experte und ein führender Science-Fiction-Autor zusammengetan, um eine zwingende Frage zu beantworten: Wie wird künstliche Intelligenz unser Leben in zwanzig Jahren verändert haben? Zehn Geschichten führen uns um die Welt und in einen neuen KI-geprägten Alltag, jeweils gefolgt von einem Realitätscheck durch Kai-Fu Lee. Ein Muss für alle, die das Potenzial künstlicher Intelligenz erleben und verstehen wollen
    Note: ; Deutsch
    Language: German
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  • 5
    Book
    Book
    Hannover : Fachrichtung Geodäsie und Geoinformatik, Univ. Hannover
    Show associated volumes
    UID:
    kobvindex_GFZ176793534X
    Format: 155 Seiten , Illustrationen, Diagramme
    ISBN: 978-3-7696-5279-6 , 9783769652796
    ISSN: 0174-1454
    Series Statement: Wissenschaftliche Arbeiten der Fachrichtung Geodäsie und Geoinformatik der Leibniz Universität Hannover Nr. 369
    Note: Auch veröffentlicht in: Deutsche Geodätische Kommission bei der Bayerischen Akademie der Wissenschaften, Reihe C, Nr. 867, München 2021, ISBN 978-3-7696-5279-6 , Dissertation, Gottfried Wilhelm Leibniz Universität Hannover, 2021 , Contents 1. Introduction 1.1. Motivation 1.2. Main Contributions 1.3. Thesis Outline 2. Basics 2.1. Feature based Image Matching 2.1.1. Overview: What is Feature based Image Matching? 2.1.2. Desired Properties for Detected Features and Descriptors 2.1.3. Scale-Invariant Feature Detection 2.1.4. Feature Affine Shape Estimation 2.1.5. Feature Orientation Assignment 2.1.6. Feature Description 2.1.7. Descriptor Matching 2.2. Convolutional Neural Network (CNN) 2.2.1. Architecture of CNN 2.2.2. Training of CNN 2.3. Siamese Convolutional Neural Network 3. Related Work 3.1. Local Feature Detection 3.1.1. Translation and Rotation Invariant Features 3.1.2. Scale Invariant Features 3.1.3. Detectors based on a Comparison of Grey Values or Saliency 3.1.4. Detectors based on Machine Learning 3.2. Feature Orientation and Affine Shape Estimation 3.2.1. Orientation Assignment 3.2.2. Affine Shape Estimation 3.3. Local Feature Description 3.3.1. Hand Crafted Descriptors 3.3.2. Machine Learning based Descriptors 3.4. An Application: Orientation of Oblique Aerial Images 3.5. Discussion 3.5.1. Orientation Assignment and Affine Shape Estimation 3.5.2. Descriptor Learning 3.5.3. An Aerial Photogrammetric Benchmark 3.5.4. Ability to Transfer Learned Modules 4. Deep Learning Feature Representation 4.1. Overview of the Methodology 4.2. Descriptor Learning using Active Weak Match Finder - WeMNet 4.2.1. Descriptor Learning Architecture 4.2.2. Generation of Training Pairs 4.2.3. Loss Function 4.2.4. Weak Match Branch 4.3. Self Supervised Feature Affine Shape Learning - MoNet 4.3.1. Affine Transformation Decomposition 4.3.2. Self Supervised Affine Shape Estimation Module 4.4. Self Supervised Orientation Assignment Module - MGNet 4.5. Full Affine Estimation Network - Full-AfFNet 4.5.1. Full Affine Network 4.5.2. Training Loss 4.5.3. Data Augmentation 4.6. Inference based on the Trained Networks 4.7. Discussion 4.7.1. Descriptor Learning 4.7.2. Affine Shape Estimation 4.7.3. Orientation Assignment Learning 4.7.4. The Inference Pipeline 5. Experiments and Results 5.1. Datasets 5.1.1. Datasets for Training 5.1.2. Datasets for Testing 5.2. Evaluation and Analysis Criteria 5.2.1. Task A: Patch based Image Matching 5.2.2. Task B: Descriptor Distance Analysis 5.2.3. Task C: Feature based Image Matching 5.2.4. Task D: Image Orientation 5.2.5. Summary of Tasks and Involved Datasets 5.3. Descriptor Learning and Patch Based Image Matching 5.3.1. Parameter Study for WeMNet 5.3.2. Comparison to Related Work 5.4. Descriptor Distance Analysis 5.4.1. Translation 5.4.2. Rotation 5.4.3. Affine Shape Transformation 5.5. Image Matching Analysis 5.5.1. Parameter Study for Affine Shape Learning 5.5.2. Image Matching for Rotation Dataset 5.5.3. Image Matching for Hpatches Affine Dataset 5.6. Image Orientation 5.6.1. Determination of Image Orientation 5.6.2. Experiment Setup Details 5.6.3. Orientation Result of Different Blocks 5.6.4. Matching Quality Analysis 6. Discussion 6.1. Descriptor Learning and Patch Based Image Matching 6.1.1. Parameter Study 6.1.2. Comparison to Related Works 6.2. Descriptor Distance Analysis 6.2.1. Translation 6.2.2. Rotation 6.2.3. Affine Shape Transformation 6.3. Feature based Image Matching 6.3.1. Parameter Study 6.3.2. Rotation Set 6.3.3. Affine Set 6.4. Image Orientation 7. Conclusion and Outlook Bibliography A. Affine Shape Adaptation Theory A.l. transformation of affine Gaussian scale-space A.2. Local affine distortion measurement A.3. More affine transformation
    In: Wissenschaftliche Arbeiten der Fachrichtung Geodäsie und Geoinformatik der Leibniz Universität Hannover
    Language: English
    Keywords: Hochschulschrift
    Author information: Chen, Lin 1987-
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